The Temporal Convolutional model[1]} architecture consists of 1-dimensional convolutional layer followed by a batch normalisation layer, ReLU and dropout (Figure REF ). This arrangement is followed by \(N\)  number of residual blocks where each of consists of a combination of 1-dimensional convolution layer, a batch norm layer, ReLU and dropout followed repeatedly by the same combination again. Finally there exists another 1-dimensional convolutional layer before the output layer.
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